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- W2156291239 abstract "We consider distributed applications that continuously stream data across the network, where data needs to be aggregated and processed to produce a 'useful' stream of updates. Centralized approaches to performing data aggregation suffer from high communication overheads, lack of scalability, and unpredictably high processing workloads at central servers. This paper describes a scalable and efficient solution to distributed stream management based on (1) resource-awareness, which is middleware-level knowledge of underlying network and processing resources, (2) overlay-based in-network data aggregation, and (3) high-level programming constructs to describe data-flow graphs for composing useful streams. Technical contributions include a novel algorithm based on resource-aware network partitioning to support dynamic deployment of dataflow graph components across the network, where efficiency of the deployed overlay is maintained by making use of partition-level resource-awareness. Contributions also include efficient middleware-based support for component deployment, utilizing runtime code generation rather than interpretation techniques, thereby addressing both high performance and resource-constrained applications. Finally, simulation experiments and benchmarks attained with actual operational data corroborate this paper's claims." @default.
- W2156291239 created "2016-06-24" @default.
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- W2156291239 date "2005-01-01" @default.
- W2156291239 modified "2023-10-16" @default.
- W2156291239 title "Resource-Aware Distributed Stream Management Using Dynamic Overlays" @default.
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- W2156291239 doi "https://doi.org/10.1109/icdcs.2005.69" @default.
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